Goal-directed weakening of abstract interpretation results

Abstract

One proposal for automatic construction of proofs about programs is to combine Hoare logic and abstract interpretation. Constructing proofs is in Hoare logic. Discovering programs' invariants is done by abstract interpreters.One problem of this approach is that abstract interpreters often compute invariants that are not needed for the proof goal. The reason is that the abstract interpreter does not know what the proof goal is, so it simply tries to find as strong invariants as possible. These unnecessary invariants increase the size of the constructed proofs. Unless the proof-construction phase is notified which invariants are not needed, it blindly proves all the computed invariants.In this article, we present a framework for designing algorithms, called abstract-value slicers, that slice out unnecessary invariants from the results of forward abstract interpretation. The framework provides a generic abstract-value slicer that can be instantiated into a slicer for a particular abstract interpretation. Such an instantiated abstract-value slicer works as a postprocessor to an abstract interpretation in the whole proof-construction process, and notifies to the Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or direct commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 ( next proof-construction phase which invariants it does not have to prove. Using the framework, we designed an abstract-value slicer for an existing relational analysis and applied it on programs. In this experiment, the slicer identified 62%-81% of the computed invariants as unnecessary, and resulted in 52%-84% reduction in the size of constructed proofs.

An Abstract Model of Certificate Translation

“…In a follow up of [Seo et al 2003], Seo, Yang, Yi and Han [Seo et al 2007] develop slicing methods to remove unused parts of the specification, simplifying the next proof-producing phase.…”

Computing Stack Maps with Interfaces

“…Such pruning algorithms were independently studied by Seo, Yang, Yi and Han [SYYH07]. The problem that we consider here is different: the goal is not to get a maximal witness in a given lattice, but to get a witness without conjunction, a property that is not monotone.…”